Country-Level Seasonal Threat Profiles Operationalizing Seasonal Forecasts into Decision-Relevant Risk Metrics

This technical note - prepared by the International Research Institute for Climate and Society (IRI), Earth Institute at Columbia University and World Bank's Global Crisis Risk Platform (GCRP) - details methodological steps to analyze seasonal precipitation anomaly forecasts, and integrate outc...

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Bibliographic Details
Corporate Author: World Bank Group
Format: eBook
Language:English
Published: Washington, D.C The World Bank 2022
Series:Other papers
Subjects:
Online Access:
Collection: World Bank E-Library Archive - Collection details see MPG.ReNa
Description
Summary:This technical note - prepared by the International Research Institute for Climate and Society (IRI), Earth Institute at Columbia University and World Bank's Global Crisis Risk Platform (GCRP) - details methodological steps to analyze seasonal precipitation anomaly forecasts, and integrate outcomes into emerging risk information at country levels. As part of the Global Crisis Risk Platform's work on compound risk, a prototype classification system is presented for showcasing country-level seasonal risk information that is tailored to national decision-making environments. Three prototypes are detailed, each with increasing levels of complexity and input data. Prototype 1.0 presents a country level threat profile based only on precipitation anomalies from IRI seasonal forecast output, based on precipitation forecasts anomalies, or deviations from 'climate normal' conditions, over the next three months. Prototype 1.1 builds off 1.0, with integration of persistence in dry conditions by combining observed precipitation anomalies over recent months with forecast information. Finally, Prototype 1.2 includes criteria related to both population exposure and land use to enhance Prototype 1.1. For each prototype a justification for the methodology is presented, including a rationale for both the input data used and definition of thresholds. Acknowledging the influence of method selection and threshold definition has on outputs, the methodology systematically assesses sensitivity of these critical variables by noting how Prototype outputs change over time, using 12 consecutive forecasts from April 2020 to March 2021